In the field of prosthetics and orthotics (P&O), lower limb devices, such as prostheses, exist that allow increased mobility for amputees or other individuals without a lower limb (herein referred to generally as “amputees”). Lower limb devices, such as orthoses and exoskeletons, allow increased mobility for individuals who have suffered a stroke, a spinal cord injury, or other condition impairing the lower limbs, or who suffer a disease, such as peripheral neuropathy, that limits the full use of one or more lower limbs.
Some lower limb devices are passive, requiring amputees to expend far more energy performing tasks, such as standing, walking, running, or climbing stairs, than a fully-limbed individual would otherwise expend. Other lower limb devices are powered, offering amputees the promise of regaining the ability to perform all tasks that a sound-limbed individual can perform, including standing, walking, running, and climbing stairs. A powered lower limb device uses motors to apply torques to one or more joints in the limb, causing the joint to flex or stiffen with applied levels of power and therefore assisting a user's movement during a task. The pattern of motion repeating from step to step during a task or other locomotion is called a “gait.” A gait may be divided into a “stance” phase, wherein the foot of the leg is in contact with the ground, and a “swing” phase, wherein the foot of the leg is not in contact with the ground. The stance phase and the swing phase each may be divided into more discrete phases; for instance, swing phase may be divided into early swing phase (knee flexion) and late swing phase (knee extension).
Powered lower limb devices include a microprocessor that is programmed with a control system for the control of the device. Control systems known in the art for powered lower limb prostheses rely on various strategies. One control system relies on information from sensors coupled to the lower limb device, which provide real-time information about the present joint angles, velocities, and torques when the device is in operation. The control system compares information received from sensors to a look-up table of desired joint angles, velocities, or torques over time. One disadvantage of this system is that it is not adaptable to varying tasks or conditions. The look-up table is based on a gait cycle that has been divided into multiple time periods, each termed “phases,” that have observable behaviors. An example of a “phase” is when the ankle pushes off at the end of a step cycle, as shown in FIG. 1. In the prior art, a prosthetic leg sequentially mimics human behavior by implementing a different control model for each discrete phase of gait. FIG. 1 further shows how the velocity, angle, and torque depend on a time variable set in each phase of the gait cycle, in the prior art. This prior art approach requires each controller to be manually tuned and is not robust to external perturbations that push joint kinematics (i.e., angles and velocities) forward or backward in the gait cycle, which cause the wrong controller to be used.
Prior art systems that rely on segmentation of the gait cycle employ a variety of control strategies, which may enforce different reference trajectories, joint impedances (the “impedance” of a joint being a measurement of its stiffness/viscosity), and/or reflex models, based on discrete phases of the gait cycle. Such control systems are disclosed in the following articles, which are incorporated by reference: F. Sup, A. Bohara, and M. Goldfarb, “Design and control of a powered transfemoral prosthesis,” Int J Rob Res, vol. 27, pp. 263-273, Feb. 1, 2008; F. Sup, H. A. Varol, and M. Goldfarb, “Upslope walking with a powered knee and ankle prosthesis: initial results with an amputee subject,” IEEE transactions on neural systems and rehabilitation engineering, vol. 19, pp. 71-8, February 2011; M. F. Eilenberg, H. Geyer, and H. Herr, “Control of a powered ankle-foot prosthesis based on a neuromuscular model,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 18, pp. 164-73, April 2010; and K. A. Shorter, G. F. Kogler, E. Loth, W. K. Durfee, and E. T. Hsiao-Wecksler, “A portable powered ankle-foot orthosis for rehabilitation,” J Rehabil Res Dev, vol. 48, pp. 459-72, 2011. One disadvantage of these control systems is that a highly-trained clinician must spend significant amounts of time to finely tune multiple control parameters for each individual user. These powered lower limb prostheses have many parameters that must be tuned for stance, including parameters relating to sequential impedance control, a joint muscle model, or lookup tables for tracking human data. Having multiple parameters that require precise tuning contributes substantially to the expense of a powered lower limb device.
Another disadvantage of current powered lower limb devices is that the control strategies do not fully account for the natural walking shape that a natural lower limb employs during tasks. As a result, powered lower limb devices employing such control strategies can cause discomfort and instability to their users. The natural walking shape can be approximated by the “effective shape.” The effective shape is the trajectory of the center of pressure (or “COP”, described below) mapped into a moving reference frame attached to the stance leg. The effective shape is called the rollover shape during walking. For a rigid object, such as a metal wheel, the effective shape is its actual geometry. Objects that are not rigid, such as an ankle or other joint, have a variable effective shape that can be controlled within a local coordinate frame, such as that of the shank or thigh. The effective shape of a human's able-bodied lower limb remains invariant across many conditions, including heel height, walking speed, and body weight. In other words, the effective shape does not change in response to changes in these conditions. The effective shape of an able-bodied lower limb changes between different tasks. For example, the curvature of the effective shape of a lower limb when performing a walking task differs from the curvature of the effective shape of a lower limb when performing a stationary standing task. Likewise, upstairs climbing requires yet another different effective shape. Each effective shape can be characterized by the curvature of the COP trajectory with respect to a reference frame attached to the stance leg. The COP is the point on the plantar sole of a foot where the cumulative reaction force is imparted against the ground. See A. H. Hansen and D. S. Childress, “Investigations of roll-over shape: implications for design, alignment, and evaluation of ankle-foot prostheses and orthoses,” Disabil Rehabil, vol. 32, pp. 2201-9, 2010, which is incorporated by reference.
Certain prior art systems make limited use of the COP. The “Shape & Roll” is a passive foot prosthesis, the bottom of which is made with rubber or other flexible material, with periodic gaps in material across the bottom of the sole. When an amputee walks on the Shape & Roll, the pressure at the COP compresses the rubber or other flexible material into the gaps, enforcing an effective shape that mirrors the natural walking shape of a sound leg. In addition to being a passive system, the Shape & Roll foot cannot enforce more than one effective shape, limiting its usability for individuals who want to perform more than one task (such as walking and climbing stairs). The Shape & Roll foot does not provide knee control, for above-knee amputees. The Genium prosthetic leg is a passive, microcontrolled leg that uses the COP during the user configuration process but does not use COP for active control. Certain humanoid robots employ strategies that attempt to control the COP so that it stays near the center of the foot, away from the edges, in order to prevent foot rotation and thus prevent falls, but does not measure the COP as a phase variable for controlling the progression of joint patterns. Bipedal robots are known that can walk, run, and climb stairs using a control framework that uses sensor measurements and actuators to produce joint torques. See E. R. Westervelt, J. W. Grizzle, C. Chevallereau, J. H. Choi, and B. Morris, Feedback Control of Dynamic Bipedal Robot Locomotion (New York, N.Y.: CRC Press, 2007), incorporated by reference. The control system employed by these bipedal robots uses a monotonic physical variable to control movement. The monotonic variable serves as a unique representation of the phase (or timing) in the gait cycle (the period between ground-strike events of the same leg). Therefore, the phase variable parameterizes a nonlinear control model to create appropriate phase-specific behaviors. Calculation of the monotonic variable relies on data from joint encoders for multiple joints of the robot. Such a strategy is not feasible in the design of a lower limb device like a prosthesis, orthosis, or exoskeleton, where clinical application of the device precludes attachment of multiple sensors to the sound joints of the user, significantly limiting measurement and control as a result.
One prior art prosthetic ankle employs a combination of the shank angle and velocity to track able-bodied human data on the basis of a look-up table of pre-defined reference trajectories. As a result, the ankle is not adaptable to varying conditions or tasks. The ankle also relies on measurements from gyroscopes, which are difficult to implement due to sensor drift and delay from filtering. The ankle cannot be used effectively by above-knee amputees, who do not have a knee joint.
Other prior art prostheses use mechanical or hydraulic means to cause the knee joint to move in response to a force initiated at the ankle One system, known as the Hydracadence knee (Proteor: Dijon, France), relies on the physical force of fluid pushed between ankle and knee for joint control.